Thu, 12 Apr 2018

Package rnr updated to version 0.2.0 with previous version 0.1.0 dated 2018-02-27

Title: Rosenbaum and Rubin Sensitivity
Description: Apply sensitivity analysis for offline policy evaluation, as implemented in Jung et al. (2017) <arXiv:1702.04690> based on Rosenbaum and Rubin (1983) <http://www.jstor.org/stable/2345524>.
Author: Jongbin Jung
Maintainer: Jongbin Jung <me@jongbin.com>

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Package MixSIAR updated to version 3.1.10 with previous version 3.1.9 dated 2018-03-30

Title: Bayesian Mixing Models in R
Description: Creates and runs Bayesian mixing models to analyze biological tracer data (i.e. stable isotopes, fatty acids), which estimate the proportions of source (prey) contributions to a mixture (consumer). 'MixSIAR' is not one model, but a framework that allows a user to create a mixing model based on their data structure and research questions, via options for fixed/ random effects, source data types, priors, and error terms. 'MixSIAR' incorporates several years of advances since 'MixSIR' and 'SIAR', and includes both GUI (graphical user interface) and script versions.
Author: Brian Stock [cre, aut], Brice Semmens [aut], Eric Ward [ctb], Andrew Parnell [ctb], Andrew Jackson [ctb], Donald Phillips [ctb]
Maintainer: Brian Stock <b1stock@ucsd.edu>

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Package clhs updated to version 0.6-0 with previous version 0.5-7 dated 2017-09-11

Title: Conditioned Latin Hypercube Sampling
Description: Conditioned Latin hypercube sampling, as published by Minasny and McBratney (2006) <DOI:10.1016/j.cageo.2005.12.009>. This method proposes to stratify sampling in presence of ancillary data. An extension of this method, which propose to associate a cost to each individual and take it into account during the optimisation process, is also proposed (Roudier et al., 2012, <DOI:10.1201/b12728-46>).
Author: Pierre Roudier [aut, cre], Colby Brugnard [ctb], Dylan Beaudette [ctb]
Maintainer: Pierre Roudier <roudierp@landcareresearch.co.nz>

Diff between clhs versions 0.5-7 dated 2017-09-11 and 0.6-0 dated 2018-04-12

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Package RZigZag updated to version 0.1.5 with previous version 0.1.4 dated 2017-10-28

Title: Zig-Zag Sampler
Description: Implements the Zig-Zag algorithm with subsampling and control variates (ZZ-CV) of (Bierkens, Fearnhead, Roberts, 2016) <arXiv:1607.03188> as applied to Bayesian logistic regression, as well as basic Zig-Zag for a Gaussian target distribution.
Author: Joris Bierkens
Maintainer: Joris Bierkens <joris.bierkens@tudelft.nl>

Diff between RZigZag versions 0.1.4 dated 2017-10-28 and 0.1.5 dated 2018-04-12

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Package clampSeg updated to version 1.0-3 with previous version 1.0-1 dated 2017-06-07

Title: Idealisation of Patch Clamp Recordings
Description: Allows for idealisation of patch clamp recordings by implementing the non-parametric JUmp Local dEconvolution Segmentation (JULES) filter, see F. Pein, I. Tecuapetla-Gómez, O. Schütte, C. Steinem, and A. Munk (2017) <arXiv:1706.03671>.
Author: Pein Florian [aut, cre], Thomas Hotz [ctb], Inder Tecuapetla-Gómez [ctb], Timo Aspelmeier [ctb]
Maintainer: Pein Florian <fpein@uni-goettingen.de>

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Package BALCONY updated to version 0.2.0 with previous version 0.1.8 dated 2017-11-28

Title: Better ALignment CONsensus analYsis
Description: Facilitates the evolutionary analysis and structure conservation study of specified amino acids in proteins.
Author: Michal Stolarczyk & Alicja Pluciennik
Maintainer: Michal Stolarczyk <stolarczyk.michal93@gmail.com>

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Package aqp updated to version 1.16 with previous version 1.15 dated 2017-11-12

Title: Algorithms for Quantitative Pedology
Description: The Algorithms for Quantitative Pedology (AQP) project was started in 2009 to organize a loosely-related set of concepts and source code on the topic of soil profile visualization, aggregation, and classification into this package (aqp). Over the past 8 years, the project has grown into a suite of related R packages that enhance and simplify the quantitative analysis of soil profile data. Central to the AQP project is a new vocabulary of specialized functions and data structures that can accommodate the inherent complexity of soil profile information; freeing the scientist to focus on ideas rather than boilerplate data processing tasks <doi:10.1016/j.cageo.2012.10.020>. These functions and data structures have been extensively tested and documented, applied to projects involving hundreds of thousands of soil profiles, and deeply integrated into widely used tools such as SoilWeb <https://casoilresource.lawr.ucdavis.edu/soilweb-apps/>. Components of the AQP project (aqp, soilDB, sharpshootR, soilReports packages) serve an important role in routine data analysis within the USDA-NRCS Soil Science Division. The AQP suite of R packages offer a convenient platform for bridging the gap between pedometric theory and practice.
Author: Dylan Beaudette [aut, cre], Pierre Roudier [aut, ctb]
Maintainer: Dylan Beaudette <dylan.beaudette@ca.usda.gov>

Diff between aqp versions 1.15 dated 2017-11-12 and 1.16 dated 2018-04-12

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Package spam updated to version 2.1-4 with previous version 2.1-3 dated 2018-03-28

Title: SPArse Matrix
Description: Set of functions for sparse matrix algebra. Differences with other sparse matrix packages are: (1) we only support (essentially) one sparse matrix format, (2) based on transparent and simple structure(s), (3) tailored for MCMC calculations within G(M)RF. (4) and it is fast and scalable (with the extension package spam64).
Author: Reinhard Furrer [aut, cre], Florian Gerber [ctb], Roman Flury [ctb], Daniel Gerber [ctb], Kaspar Moesinger [ctb], Youcef Saad [ctb] (SPARSEKIT http://www-users.cs.umn.edu/~saad/software/SPARSKIT/), Esmond G. Ng [ctb] (Fortran Cholesky routines), Barry W. Peyton [ctb] (Fortran Cholesky routines), Joseph W.H. Liu [ctb] (Fortran Cholesky routines), Alan D. George [ctb] (Fortran Cholesky routines)
Maintainer: Reinhard Furrer <reinhard.furrer@math.uzh.ch>

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Package PowerTOST updated to version 1.4-7 with previous version 1.4-6 dated 2017-08-17

Title: Power and Sample Size Based on Two One-Sided t-Tests (TOST) for (Bio)Equivalence Studies
Description: Contains functions to calculate power and sample size for various study designs used for bioequivalence studies. See function known.designs() for study designs covered. Moreover the package contains functions for power and sample size based on 'expected' power in case of uncertain (estimated) variability and/or uncertain theta0. ----- Added are functions for the power and sample size for the ratio of two means with normally distributed data on the original scale (based on Fieller's confidence ('fiducial') interval). ----- Contains further functions for power and sample size calculations based on non-inferiority t-test. This is not a TOST procedure but eventually useful if the question of 'non-superiority' must be evaluated. The power and sample size calculations based on non-inferiority test may also performed via 'expected' power in case of uncertain (estimated) variability and/or uncertain theta0. ----- Contains functions power.scABEL() and sampleN.scABEL() to calculate power and sample size for the BE decision via scaled (widened) BE acceptance limits (EMA recommended) based on simulations. Contains also functions scABEL.ad() and sampleN.scABEL.ad() to iteratively adjust alpha in order to maintain the overall consumer risk in ABEL studies and adapt the sample size for the loss in power. Contains further functions power.RSABE() and sampleN.RSABE() to calculate power and sample size for the BE decision via reference scaled ABE criterion according to the FDA procedure based on simulations. Contains further functions power.NTIDFDA() and sampleN.NTIDFDA() to calculate power and sample size for the BE decision via the FDA procedure for NTID's based on simulations. Contains further functions power.HVNTID() and sampleN.HVNTID() to calculate power and sample size for the BE decision via the FDA procedure for highly variable NTID's (see FDA Dabigatran / rivaroxaban guidances) ----- Contains functions for power analysis of a sample size plan for ABE (pa.ABE()), scaled ABE (pa.scABE()) and scaled ABE for NTID's (pa.NTIDFDA()) analysing power if deviating from assumptions of the plan. ----- Contains further functions for power calculations / sample size estimation for dose proportionality studies using the Power model.
Author: Detlew Labes [aut, cre], Helmut Schuetz [aut], Benjamin Lang [aut]
Maintainer: Detlew Labes <DetlewLabes@gmx.de>

Diff between PowerTOST versions 1.4-6 dated 2017-08-17 and 1.4-7 dated 2018-04-12

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Package PreciseSums updated to version 0.3 with previous version 0.1 dated 2017-11-14

Title: Accurate Floating Point Sums and Products
Description: Most of the time floating point arithmetic does approximately the right thing. When adding sums or having products of numbers that greatly differ in magnitude, the floating point arithmetic may be incorrect. This package implements the Kahan (1965) sum <doi:10.1145/363707.363723>, Neumaier (1974) sum <doi:10.1002/zamm.19740540106>, pairwise-sum (adapted from 'NumPy', See Castaldo (2008) <doi:10.1137/070679946> for a discussion of accuracy), and arbitrary precision sum (adapted from the fsum in 'Python' ; Shewchuk (1997) <http://www.cs.berkeley.edu/~jrs/papers/robustr.pdf>). In addition, products are changed to long double precision for accuracy, or changed into a log-sum for accuracy.
Author: Matthew Fidler [aut, cre, cph], Raymond Hettinger [cph, aut], Jonathan Shewchuk [cph, aut], Julian Taylor [cph, aut], Nathaniel Smith [cph, aut], NumPy Team [cph], Python Team [cph]
Maintainer: Matthew Fidler <matthew.fidler@gmail.com>

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Package brt updated to version 1.2.0 with previous version 1.1.0 dated 2017-03-03

Title: Biological Relevance Testing
Description: Analyses of large-scale -omics datasets commonly use p-values as the indicators of statistical significance. However, considering p-value alone neglects the importance of effect size (i.e., the mean difference between groups) in determining the biological relevance of a significant difference. Here, we present a novel algorithm for computing a new statistic, the biological relevance testing (BRT) index, in the frequentist hypothesis testing framework to address this problem.
Author: Le Zheng[aut], Peng Yu[aut, cre]
Maintainer: Le Zheng <lzheng.chn@gmail.com>

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Package spc updated to version 0.6.0 with previous version 0.5.4 dated 2017-10-05

Title: Statistical Process Control -- Calculation of ARL and Other Control Chart Performance Measures
Description: Evaluation of control charts by means of the zero-state, steady-state ARL (Average Run Length) and RL quantiles. Setting up control charts for given in-control ARL. The control charts under consideration are one- and two-sided EWMA, CUSUM, and Shiryaev-Roberts schemes for monitoring the mean or variance of normally distributed independent data. ARL calculation of the same set of schemes under drift (in the mean) are added. Eventually, all ARL measures for the multivariate EWMA (MEWMA) are provided.
Author: Sven Knoth
Maintainer: Sven Knoth <Sven.Knoth@gmx.de>

Diff between spc versions 0.5.4 dated 2017-10-05 and 0.6.0 dated 2018-04-12

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Package phyreg updated to version 1.0.2 with previous version 1.0.1 dated 2018-04-08

Title: The Phylogenetic Regression of Grafen (1989)
Description: Provides general linear model facilities (single y-variable, multiple x-variables with arbitrary mixture of continuous and categorical and arbitrary interactions) for cross-species data. The method is, however, based on the nowadays rather uncommon situation in which uncertainty about a phylogeny is well represented by adopting a single polytomous tree. The theory is in A. Grafen (1989, Proc. R. Soc. B 326, 119-157) and aims to cope with both recognised phylogeny (closely related species tend to be similar) and unrecognised phylogeny (a polytomy usually indicates ignorance about the true sequence of binary splits).
Author: Alan Grafen
Maintainer: Alan Grafen <alan.grafen@sjc.ox.ac.uk>

Diff between phyreg versions 1.0.1 dated 2018-04-08 and 1.0.2 dated 2018-04-12

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Package jose updated to version 0.2 with previous version 0.1 dated 2016-05-27

Title: JavaScript Object Signing and Encryption
Description: Read and write JSON Web Keys (JWK, rfc7517), generate and verify JSON Web Signatures (JWS, rfc7515) and encode/decode JSON Web Tokens (JWT, rfc7519). These standards provide modern signing and encryption formats that are the basis for services like OAuth 2.0 or LetsEncrypt and are natively supported by browsers via the JavaScript WebCryptoAPI.
Author: Jeroen Ooms [aut, cre] (<https://orcid.org/0000-0002-4035-0289>)
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>

Diff between jose versions 0.1 dated 2016-05-27 and 0.2 dated 2018-04-12

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Package yuima updated to version 1.7.10 with previous version 1.6.8 dated 2017-08-16

Title: The YUIMA Project Package for SDEs
Description: Simulation and Inference for SDEs and Other Stochastic Processes.
Author: YUIMA Project Team
Maintainer: Stefano M. Iacus <stefano.iacus@unimi.it>

Diff between yuima versions 1.6.8 dated 2017-08-16 and 1.7.10 dated 2018-04-12

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 32 files changed, 3375 insertions(+), 3117 deletions(-)

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New package sokoban with initial version 0.1.0
Package: sokoban
Type: Package
Title: Sokoban Game
Version: 0.1.0
Author: Zhaoliang He <1024299329@qq.com>, Linsui Deng <1175520015@qq.com>, Kaiwen Tan <913596401@qq.com>
Maintainer: Zhaoliang He <1024299329@qq.com>
Description: Interactively play a game of sokoban ,which has nine game levels.Sokoban is a type of transport puzzle, in which the player pushes boxes or crates around in a warehouse, trying to get them to storage locations.
License: GPL
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2018-04-10 04:08:51 UTC; Administrator
Repository: CRAN
Date/Publication: 2018-04-12 15:44:33 UTC

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Package replyr updated to version 0.9.4 with previous version 0.9.3 dated 2018-04-03

Title: Patches to Use 'dplyr' on Remote Data Sources
Description: Patches to use 'dplyr' on remote data sources ('SQL' databases, 'Spark' 2.0.0 and above) in a reliable "generic" fashion (generic meaning user code works similarly on all such sources, without needing per-source adaption). Due to the fluctuating nature of 'dplyr'/'dbplyr'/'rlang' 'APIs' this package is going into maintenance mode. Most of the 'replyr' functions are already done better by one of the non-monolithic replacement packages: 'wrapr', 'seplyr', 'rquery', or 'cdata'.
Author: John Mount [aut, cre], Nina Zumel [aut], Win-Vector LLC [cph]
Maintainer: John Mount <jmount@win-vector.com>

Diff between replyr versions 0.9.3 dated 2018-04-03 and 0.9.4 dated 2018-04-12

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New package rcube with initial version 0.1
Package: rcube
Type: Package
Title: Simulations and Visualizations of Rubik's Cube (with Mods)
Version: 0.1
Date: 2018-04-09
Author: Wojciech Rosa
Maintainer: Wojciech Rosa <w.rosa@pollub.pl>
Description: Provides simplified methods for managing classic Rubik's cubes and many other modifications of it (such as NxNxN size cubes, void cubes and 8-coloured cubes - so called octa cubes). Includes functions of handling special syntax for managing such cubes; and different approach to plotting 3D cubes without using external libraries (for example OpenGL).
License: GPL-3
LazyData: TRUE
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-04-12 13:20:20 UTC; wojci
Repository: CRAN
Date/Publication: 2018-04-12 15:51:11 UTC

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Package discSurv updated to version 1.3.1 with previous version 1.1.7 dated 2017-03-13

Title: Discrete Time Survival Analysis
Description: Provides data transformations, estimation utilities, predictive evaluation measures and simulation functions for discrete time survival analysis.
Author: Thomas Welchowski <welchow@imbie.meb.uni-bonn.de> and Matthias Schmid <matthias.schmid@imbie.uni-bonn.de>
Maintainer: Thomas Welchowski <welchow@imbie.meb.uni-bonn.de>

Diff between discSurv versions 1.1.7 dated 2017-03-13 and 1.3.1 dated 2018-04-12

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Package cem updated to version 1.1.19 with previous version 1.1.17 dated 2015-08-19

Title: Coarsened Exact Matching
Description: Implementation of the Coarsened Exact Matching algorithm.
Author: Iacus, Stefano M., King, Gary, Porro, Giuseppe
Maintainer: Stefano M. Iacus <stefano.iacus@unimi.it>

Diff between cem versions 1.1.17 dated 2015-08-19 and 1.1.19 dated 2018-04-12

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Package labstatR updated to version 1.0.9 with previous version 1.0.8 dated 2015-08-19

Title: Libreria Del Laboratorio Di Statistica Con R
Description: Insieme di funzioni di supporto al volume "Laboratorio di Statistica con R", Iacus-Masarotto, MacGraw-Hill Italia, 2006. This package contains sets of functions defined in "Laboratorio di Statistica con R", Iacus-Masarotto, MacGraw-Hill Italia, 2006. Function names and docs are in italian as well.
Author: Stefano M.Iacus <stefano.iacus@unimi.it> and Guido Masarotto <guido@sirio.stat.unipd.it>
Maintainer: Stefano M.Iacus <stefano.iacus@unimi.it>

Diff between labstatR versions 1.0.8 dated 2015-08-19 and 1.0.9 dated 2018-04-12

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Package rtip updated to version 1.1.1 with previous version 1.1.0 dated 2018-02-20

Title: Inequality, Welfare and Poverty Indices and Curves using the EU-SILC Data
Description: R tools to measure and compare inequality, welfare and poverty using the EU statistics on income and living conditions surveys.
Author: Angel Berihuete [aut, cre], Carmen Dolores Ramos [aut], Miguel Angel Sordo [aut]
Maintainer: Angel Berihuete <angel.berihuete@uca.es>

Diff between rtip versions 1.1.0 dated 2018-02-20 and 1.1.1 dated 2018-04-12

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Package pubmed.mineR updated to version 1.0.12 with previous version 1.0.11 dated 2017-09-12

Title: Text Mining of PubMed Abstracts
Description: Text mining of PubMed Abstracts (text and XML) from <http://www.ncbi.nlm.nih.gov/pubmed>.
Author: Jyoti Rani, S.Ramachandran, Ab Rauf Shah
Maintainer: S. Ramachandran <ramuigib@gmail.com>

Diff between pubmed.mineR versions 1.0.11 dated 2017-09-12 and 1.0.12 dated 2018-04-12

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Package prediction updated to version 0.3.2 with previous version 0.2.0 dated 2017-04-19

Title: Tidy, Type-Safe 'prediction()' Methods
Description: A one-function package containing 'prediction()', a type-safe alternative to 'predict()' that always returns a data frame. The package currently supports common model types (e.g., "lm", "glm") from the 'stats' package, as well as numerous other model classes from other add-on packages. See the README or main package documentation page for a complete listing.
Author: Thomas J. Leeper [aut, cre] (<https://orcid.org/0000-0003-4097-6326>), Carl Ganz [ctb]
Maintainer: Thomas J. Leeper <thosjleeper@gmail.com>

Diff between prediction versions 0.2.0 dated 2017-04-19 and 0.3.2 dated 2018-04-12

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 prediction-0.3.2/prediction/man/build_datalist.Rd          |   12 
 prediction-0.3.2/prediction/man/find_data.Rd               |   28 
 prediction-0.3.2/prediction/man/prediction.Rd              |  225 +++++--
 prediction-0.3.2/prediction/tests/testthat/tests-methods.R |  402 +++++++++++--
 76 files changed, 1536 insertions(+), 751 deletions(-)

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New package gimmeTools with initial version 0.1
Package: gimmeTools
Title: Supplemental Tools for the 'gimme' R Package
Version: 0.1
Authors@R: person("Stephanie", "Lane", email = "lane.stephanie.t@gmail.com", role = c("aut", "cre"))
Description: Supplemental tools for the 'gimme' R package. It contains an interactive graphical user interface, allowing for the flexible specification of a variety of both basic and advanced options. It will expand to include a variety of tools for navigating output.
Imports: shiny, shinyjs, rintrojs, easycsv, miniUI, shinyWidgets, rstudioapi, rhandsontable, magrittr
Depends: R (>= 3.1)
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
URL: https://github.com/stlane
NeedsCompilation: no
Packaged: 2018-04-05 23:08:08 UTC; stlane
Author: Stephanie Lane [aut, cre]
Maintainer: Stephanie Lane <lane.stephanie.t@gmail.com>
Repository: CRAN
Date/Publication: 2018-04-12 12:41:39 UTC

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Package CCM updated to version 1.2 with previous version 1.1 dated 2013-12-10

Title: Correlation Classification Method
Description: Classification method described in Dancik et al (2011) <doi:10.1158/0008-5472.CAN-11-2427> that classifies a sample according to the class with the maximum mean (or any other function of) correlation between the test and training samples with known classes.
Author: Garrett M. Dancik and Yuanbin Ru
Maintainer: Garrett M. Dancik <dancikg@easternct.edu>

Diff between CCM versions 1.1 dated 2013-12-10 and 1.2 dated 2018-04-12

 CHANGES            |    3 ++-
 DESCRIPTION        |   15 ++++++---------
 MD5                |    8 ++++----
 NAMESPACE          |   12 ++++++++----
 man/CCM-package.Rd |    4 ++--
 5 files changed, 22 insertions(+), 20 deletions(-)

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New package aws.translate with initial version 0.1.3
Package: aws.translate
Type: Package
Title: Client for 'AWS Translate'
Version: 0.1.3
Date: 2018-04-11
Authors@R: c(person("Thomas J.", "Leeper", role = c("aut", "cre"), email = "thosjleeper@gmail.com", comment = c(ORCID = "0000-0003-4097-6326")) )
Description: A client for 'AWS Translate' <https://aws.amazon.com/documentation/translate>, a machine translation service that will convert a text input in one language into a text output in another language.
License: GPL (>= 2)
URL: https://github.com/cloudyr/aws.translate
BugReports: https://github.com/cloudyr/aws.translate/issues
Imports: httr, jsonlite, aws.signature (>= 0.3.4)
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-04-12 00:17:23 UTC; THOMAS
Author: Thomas J. Leeper [aut, cre] (<https://orcid.org/0000-0003-4097-6326>)
Maintainer: Thomas J. Leeper <thosjleeper@gmail.com>
Repository: CRAN
Date/Publication: 2018-04-12 12:54:51 UTC

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New package aws.comprehend with initial version 0.1.2
Package: aws.comprehend
Type: Package
Title: 'AWS Comprehend' Client Package
Version: 0.1.2
Date: 2018-04-09
Authors@R: c(person("Thomas J.", "Leeper", role = c("aut", "cre"), email = "thosjleeper@gmail.com"))
Description: Client for 'AWS Comprehend' <https://aws.amazon.com/comprehend>, a cloud natural language processing service that can perform a number of quantitative text analyses, including language detection, sentiment analysis, and feature extraction.
License: GPL (>= 2)
URL: https://github.com/cloudyr/aws.comprehend
BugReports: https://github.com/cloudyr/aws.comprehend/issues
Imports: httr, jsonlite, aws.signature (>= 0.3.4)
Suggests: testthat
Encoding: UTF-8
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-04-09 20:50:13 UTC; THOMAS
Author: Thomas J. Leeper [aut, cre]
Maintainer: Thomas J. Leeper <thosjleeper@gmail.com>
Repository: CRAN
Date/Publication: 2018-04-12 12:54:27 UTC

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New package SimilaR with initial version 1.0.1
Package: SimilaR
Version: 1.0.1
Date: 2018-04-12
Title: R Source Code Similarity Evaluation
Description: An Implementation of a novel method to determine similarity of R functions based on program dependence graphs, see Bartoszuk, Gagolewski (2017) <doi:10.1109/FUZZ-IEEE.2017.8015582>. Possible use cases include plagiarism detection among students' homework assignments.
URL: http://similar.rexamine.com/
BugReports: https://github.com/bartoszukm/SimilaR/issues
Type: Package
Depends: R (>= 3.1.0), stringi
License: GPL (>= 3)
Authors@R: c( person("Maciej", "Bartoszuk", role = c("aut", "cre"), email = "bartoszuk@rexamine.com"), person("Marek", "Gagolewski", role = "aut", email = "gagolews@rexamine.com") )
Imports: Rcpp (>= 0.12.0)
Suggests: testthat
LinkingTo: Rcpp (>= 0.12.0), BH
SystemRequirements: C++11
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2018-04-12 10:06:50 UTC; bartoszukm
Author: Maciej Bartoszuk [aut, cre], Marek Gagolewski [aut]
Maintainer: Maciej Bartoszuk <bartoszuk@rexamine.com>
Repository: CRAN
Date/Publication: 2018-04-12 11:42:06 UTC

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Package VARSEDIG updated to version 1.6 with previous version 1.5 dated 2017-12-05

Title: An Algorithm for Morphometric Characters Selection and Statistical Validation in Morphological Taxonomy
Description: An algorithm which identifies the morphometric features that significantly discriminate two taxa and validates the morphological distinctness between them via a Monte-Carlo test, polar coordinates and overlap of the area under the density curve.
Author: Cástor Guisande González
Maintainer: Cástor Guisande González <castor@uvigo.es>

Diff between VARSEDIG versions 1.5 dated 2017-12-05 and 1.6 dated 2018-04-12

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 5 files changed, 41 insertions(+), 19 deletions(-)

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Package RegularizedSCA updated to version 0.5.3 with previous version 0.5.0 dated 2017-10-17

Title: Regularized Simultaneous Component Based Data Integration
Description: It performs regularized simultaneous component based data integration for multiblock data.
Author: Zhengguo Gu [aut, cre], Katrijn Van Deun [aut]
Maintainer: Zhengguo Gu <z.gu@uvt.nl>

Diff between RegularizedSCA versions 0.5.0 dated 2017-10-17 and 0.5.3 dated 2018-04-12

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 25 files changed, 139 insertions(+), 234 deletions(-)

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Package RatingScaleReduction updated to version 1.2.1 with previous version 1.2 dated 2017-10-10

Title: Rating Scale Reduction Procedure
Description: Describes a new procedure of reducing items in a rating scale called Rating Scale Reduction (RSR). The new stop criterion in RSR procedure is added (stop global max).
Author: Waldemar W. Koczkodaj,Feng Li ,Alicja Wolny-Dominiak
Maintainer: Alicja Wolny-Dominiak <alicja.wolny-dominiak@ue.katowice.pl>

Diff between RatingScaleReduction versions 1.2 dated 2017-10-10 and 1.2.1 dated 2018-04-12

 DESCRIPTION |    8 ++++----
 MD5         |    6 +++---
 R/rsr.R     |    9 +++++++--
 man/rsr.Rd  |    2 +-
 4 files changed, 15 insertions(+), 10 deletions(-)

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New package mgc with initial version 1.0
Package: mgc
Type: Package
Title: Multiscale Graph Correlation
Version: 1.0
Date: 2018-04-10
Authors@R: c(person("Eric", "Bridgeford", role = c("aut", "cre"), email = "ericwb95@gmail.com"), person("Censheng", "Shen", role="aut", email="cshen6@jhu.edu"), person("Shangsi", "Wang", role = "aut", email = "swang127@jhu.edu"), person("Joshua", "Vogelstein", role = "ths", email = "jovo@jhu.edu"))
Maintainer: Eric Bridgeford <ericwb95@gmail.com>
Description: Multiscale Graph Correlation (MGC) is a framework developed by Shen et al. (2017) <arXiv:1609.05148> that extends global correlation procedures to be multiscale; consequently, MGC tests typically require far fewer samples than existing methods for a wide variety of dependence structures and dimensionalities, while maintaining computational efficiency. Moreover, MGC provides a simple and elegant multiscale characterization of the potentially complex latent geometry underlying the relationship.
Depends: R (>= 3.4.0)
Imports: stats, SDMTools, MASS
URL: https://github.com/neurodata/mgc
Suggests: testthat, ggplot2, reshape2, knitr, rmarkdown
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-04-11 17:33:50 UTC; eric
Author: Eric Bridgeford [aut, cre], Censheng Shen [aut], Shangsi Wang [aut], Joshua Vogelstein [ths]
Repository: CRAN
Date/Publication: 2018-04-12 10:50:46 UTC

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Package marmap updated to version 1.0 with previous version 0.9.6 dated 2017-01-10

Title: Import, Plot and Analyze Bathymetric and Topographic Data
Description: Import xyz data from the NOAA (National Oceanic and Atmospheric Administration, <http://www.noaa.gov>), GEBCO (General Bathymetric Chart of the Oceans, <http://www.gebco.net>) and other sources, plot xyz data to prepare publication-ready figures, analyze xyz data to extract transects, get depth / altitude based on geographical coordinates, or calculate z-constrained least-cost paths.
Author: Eric Pante, Benoit Simon-Bouhet, and Jean-Olivier Irisson
Maintainer: Benoit Simon-Bouhet <besibo@gmail.com>

Diff between marmap versions 0.9.6 dated 2017-01-10 and 1.0 dated 2018-04-12

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New package LPWC with initial version 0.99.2
Package: LPWC
Version: 0.99.2
Date: 2018-03-31
Title: Lag Penalized Weighted Correlation for Time Series Clustering
Author: Thevaa Chandereng <chandereng@wisc.edu>, Anthony Gitter
Maintainer: Thevaa Chandereng <chandereng@wisc.edu>
Description: Computes a time series distance measure for clustering based on weighted correlation and introduction of lags. The lags capture delayed responses in a time series dataset. The timepoints must be specified. T. Chandereng, A. Gitter (2018) <doi:10.1101/292615>.
Depends: R (>= 3.0.2)
Suggests: testthat, knitr, rmarkdown
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
VignetteBuilder: knitr
URL: https://github.com/gitter-lab/LPWC
BugReports: https://github.com/gitter-lab/LPWC/issues
NeedsCompilation: no
Packaged: 2018-04-11 21:03:34 UTC; thevaasiinenchandereng
Repository: CRAN
Date/Publication: 2018-04-12 10:52:34 UTC

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Package indirect updated to version 0.2.0 with previous version 0.1.2 dated 2018-04-06

Title: Elicitation of Independent Conditional Means Priors for Generalised Linear Models
Description: Functions are provided to facilitate prior elicitation for Bayesian generalised linear models using independent conditional means priors. The package supports the elicitation of multivariate normal priors for generalised linear models. The approach can be applied to indirect elicitation for a generalised linear model that is linear in the parameters. The package is designed such that the facilitator executes functions within the R console during the elicitation session to provide graphical and numerical feedback at each design point. Various methodologies for eliciting fractiles (equivalently, percentiles or quantiles) are supported, including versions of the approach of Hosack et al. (2017) <doi:10.1016/j.ress.2017.06.011>. For example, experts may be asked to provide central credible intervals that correspond to a certain probability. Or experts may be allowed to vary the probability allocated to the central credible interval for each design point. Additionally, a median may or may not be elicited.
Author: Geoffrey R. Hosack
Maintainer: Geoff Hosack <geoff.hosack@csiro.au>

Diff between indirect versions 0.1.2 dated 2018-04-06 and 0.2.0 dated 2018-04-12

 DESCRIPTION                |    9 ++--
 MD5                        |   45 ++++++++++-----------
 R/elicit_functions.R       |   96 +++++++++++++++++++++++++--------------------
 R/fitting_functions.R      |    8 +--
 R/indirect.R               |   10 ++--
 R/plotting_functions.R     |   42 ++++++++++---------
 inst/CITATION              |    2 
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 vignettes/indirect.bib.sav |only
 24 files changed, 222 insertions(+), 187 deletions(-)

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New package aMNLFA with initial version 0.1
Package: aMNLFA
Title: Automated Fitting of Moderated Nonlinear Factor Analysis Through the 'Mplus' Program
Version: 0.1
Authors@R: c( person("Veronica", "Cole", email = "vcole@email.unc.edu", role = c("aut","cre")), person("Nisha", "Gottfredson", email = "gottfredson@email.unc.edu", role = c("aut")), person("Michael", "Giordano", email = "mgiordano@email.unc.edu", role = c("aut")), person("Tim", "Janssen", email = "tim_janssen@brown.edu", role = c("ctb")))
Description: Automated generation, running, and interpretation of moderated nonlinear factor analysis models for obtaining scores from observed variables. This package creates 'Mplus' input files which may be run iteratively to test two different types of covariate effects on items: (1) latent variable impact (both mean and variance); and (2) differential item functioning. After sequentially testing for all effects, it also creates a final model by including all significant effects after adjusting for multiple comparisons. Finally, the package creates a scoring model which uses the final values of parameter estimates to generate latent variable scores.
Depends: R (>= 3.1.0),
Imports: grDevices, graphics, stats, utils, ggplot2, MplusAutomation, reshape2, gridExtra, stringr, plyr, devtools
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-04-11 16:54:33 UTC; vcole
Author: Veronica Cole [aut, cre], Nisha Gottfredson [aut], Michael Giordano [aut], Tim Janssen [ctb]
Maintainer: Veronica Cole <vcole@email.unc.edu>
Repository: CRAN
Date/Publication: 2018-04-12 10:55:18 UTC

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New package WeibullR with initial version 1.0.5
Package: WeibullR
Version: 1.0.5
Date: 2018-4-11
Title: Weibull Analysis for Reliability Engineering
Authors@R: c(person("David", "Silkworth", email = "djsilk@openreliability.org", role = "aut"), person("Jurgen", "Symynck", role = "aut"), person("Jacob", "Ormerod", email = "jake@openreliability.org", role = "cre"), person("OpenReliability.org", role = "cph"))
Description: Life data analysis in the graphical tradition of Waloddi Weibull. Methods derived from Robert B. Abernethy (2008, ISBN 0-965306-3-2), Wayne Nelson (1982, ISBN: 9780471094586) <DOI:10.1002/0471725234>, William Q. Meeker and Lois A. Escobar (1998, ISBN: 1-471-14328-6), John I. McCool, (2012, ISBN: 9781118217986) <DOI:10.1002/9781118351994>.
License: GPL (>= 3)
Copyright: copyright (c) OpenReliability.org 2011-2018
URL: http://www.openreliability.org/weibull-r-weibull-analysis-on-r/
LazyLoad: yes
Imports: Rcpp (>= 0.11.1)
LinkingTo: Rcpp, RcppArmadillo
Author: David Silkworth [aut], Jurgen Symynck [aut], Jacob Ormerod [cre], OpenReliability.org [cph]
Maintainer: Jacob Ormerod <jake@openreliability.org>
Repository: CRAN
Repository/R-Forge/Project: weibull-r
Repository/R-Forge/Revision: 27
Repository/R-Forge/DateTimeStamp: 2018-04-11 11:07:08
Date/Publication: 2018-04-12 09:13:48 UTC
NeedsCompilation: yes
Packaged: 2018-04-11 11:25:08 UTC; rforge

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New package msigdbr with initial version 6.1.1
Package: msigdbr
Type: Package
Title: MSigDB for Multiple Organisms in a Tidy Data Format
Version: 6.1.1
Authors@R: person("Igor", "Dolgalev", email = "igor.dolgalev@nyumc.org", role = c("aut", "cre"))
Description: Provides the 'Molecular Signatures Database' (MSigDB) gene sets used with the 'Gene Set Enrichment Analysis' (GSEA) software (Subramanian et al. 2005 <doi:10.1073/pnas.0506580102>, Liberzon et al. 2015 <doi:10.1016/j.cels.2015.12.004>) for various frequently studied model organisms in a standard R data frame with key-value pairs.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://github.com/igordot/msigdbr
BugReports: https://github.com/igordot/msigdbr/issues
LazyData: true
Depends: R (>= 3.2.0), dplyr (>= 0.7.0), tibble
Imports: magrittr, rlang
Suggests: testthat, knitr, rmarkdown
RoxygenNote: 6.0.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-04-11 16:30:17 UTC; id460
Author: Igor Dolgalev [aut, cre]
Maintainer: Igor Dolgalev <igor.dolgalev@nyumc.org>
Repository: CRAN
Date/Publication: 2018-04-12 09:16:18 UTC

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Package lfl updated to version 1.4.1 with previous version 1.4 dated 2017-04-25

Title: Linguistic Fuzzy Logic
Description: Various algorithms related to linguistic fuzzy logic: mining for linguistic fuzzy association rules, composition of fuzzy relations, performing perception-based logical deduction (PbLD), and forecasting time-series using fuzzy rule-based ensemble (FRBE).
Author: Michal Burda
Maintainer: Michal Burda <michal.burda@osu.cz>

Diff between lfl versions 1.4 dated 2017-04-25 and 1.4.1 dated 2018-04-12

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 R/searchrules.R    |    2 +-
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 16 files changed, 65 insertions(+), 58 deletions(-)

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Package idem updated to version 3.5 with previous version 3.0 dated 2017-09-02

Title: Inference in Randomized Controlled Trials with Death and Missingness
Description: In randomized studies involving severely ill patients, functional outcomes are often unobserved due to missed clinic visits, premature withdrawal or death. It is well known that if these unobserved functional outcomes are not handled properly, biased treatment comparisons can be produced. In this package, we implement a procedure for comparing treatments that is based on the composite endpoint of both the functional outcome and survival. The procedure was proposed in Wang et al. (2016) <doi:10.1111/biom.12594>. It considers missing data imputation with a sensitivity analysis strategy to handle the unobserved functional outcomes not due to death.
Author: Chenguang Wang [aut, cre], Andrew Leroux [aut, cre], Elizabeth Colantuoni [aut], Daniel O Scharfstein [aut], Trustees of Columbia University [cph] (tools/make_cpp.R, R/stanmodels.R)
Maintainer: Chenguang Wang <cwang68@jhmi.edu>

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New package bayesammi with initial version 0.1.0
Package: bayesammi
Type: Package
Title: Bayesian Estimation of the Additive Main Effects and Multiplicative Interaction Model
Version: 0.1.0
Authors@R: c( person(c("Muhammad", "Yaseen"), email = "myaseen208@gmail.com", role = c("aut", "cre")) , person(c("Jose", "Crossa"), email = "j.crossa@cgiar.org", role = c("aut", "ctb")) , person(c("Sergio", "Perez-Elizalde"), email = "sergiop@colpos.mx", role = c("aut", "ctb")) , person(c("Diego", "Jarquin"), email = "diego.jarquin@gmail.com", role = c("aut", "ctb")) , person(c("Jose", "Miguel", "Cotes"), email = " ", role = c("aut", "ctb")) , person(c("Kert", "Viele"), email = " ", role = c("aut", "ctb")) , person(c("Genzhou", "Liu"), email = " ", role = c("aut", "ctb")) , person(c("Paul", "L.", " Cornelius"), email = " ", role = c("aut", "ctb")) )
Maintainer: Muhammad Yaseen <myaseen208@gmail.com>
Description: Performs Bayesian estimation of the additive main effects and multiplicative interaction (AMMI) model. The method is explained in Crossa, J., Perez-Elizalde, S., Jarquin, D., Cotes, J.M., Viele, K., Liu, G. and Cornelius, P.L. (2011) (<doi:10.2135/cropsci2010.06.0343>).
Depends: R (>= 3.1)
Imports: dplyr, ggplot2, lme4, magrittr, MASS, mvtnorm, rlang, rstiefel, scales, stats, tibble, tidyr, tmvtnorm
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Note: Department of Mathematics and Statistics, University of Agriculture Faisalabad, Faisalabad-Pakistan.
NeedsCompilation: no
Packaged: 2018-04-11 13:32:40 UTC; myaseen
Author: Muhammad Yaseen [aut, cre], Jose Crossa [aut, ctb], Sergio Perez-Elizalde [aut, ctb], Diego Jarquin [aut, ctb], Jose Miguel Cotes [aut, ctb], Kert Viele [aut, ctb], Genzhou Liu [aut, ctb], Paul L. Cornelius [aut, ctb]
Repository: CRAN
Date/Publication: 2018-04-12 09:03:23 UTC

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Package VarSelLCM updated to version 2.1.1 with previous version 2.1.0 dated 2018-03-19

Title: Variable Selection for Model-Based Clustering of Mixed-Type Data Set with Missing Values
Description: Full model selection (detection of the relevant features and estimation of the number of clusters) for model-based clustering (see reference here <doi:10.1007/s11222-016-9670-1>). Data to analyze can be continuous, categorical, integer or mixed. Moreover, missing values can occur and do not necessitate any pre-processing. Shiny application permits an easy interpretation of the results.
Author: Matthieu Marbac and Mohammed Sedki
Maintainer: Mohammed Sedki <mohammed.sedki@u-psud.fr>

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New package stratifyR with initial version 1.0-1
Package: stratifyR
Type: Package
Title: Optimal Stratification of Univariate Populations
Version: 1.0-1
Date: 2018-04-11
Authors@R: c( person("Karuna G.", "Reddy",, "reddy_k@usp.ac.fj", c("aut", "cre")), person("M. G. M.", "Khan",, "khan_mg@usp.ac.fj", "aut") )
Author: Karuna G. Reddy [aut, cre], M. G. M. Khan [aut]
Maintainer: Karuna G. Reddy <reddy_k@usp.ac.fj>
Description: This implements the stratification of univariate populations under stratified sampling designs using the method of Khan et al. (2002) <doi:10.1177/0008068320020518>, Khan et al. (2008) (<http://www.statcan.gc.ca/pub/12-001-x/2008002/article/10761-eng.pdf>) and Khan et al. (2015) <doi:10.1080/02664763.2015.1018674>. It determines the Optimum Strata Boundaries (OSB) and Optimum Sample Sizes (OSS) for the study variable, y, using the best-fit frequency distribution of a survey variable (if data is available) or a hypothetical distribution (if data is not available). The method formulates the problem of determining the OSB as mathematical programming problem which is solved by using a dynamic programming technique. If a dataset of the population is available to the surveyor, the method estimates its best-fit distribution and determines the OSB and OSS under Neyman allocation directly. When the dataset is not available, stratification is made based on the assumption that the values of the study variable, y, are available as hypothetical realizations of proxy values of y from recent surveys. Thus, it requires certain distributional assumptions about the study variable. At present, it handles stratification for the populations where the study variable follows a continuous distribution, namely, Pareto, Triangular, Right-triangular, Weibull, Gamma, Exponential, Uniform, Normal, Log-normal and Cauchy distributions.
LazyData: true
License: GPL-2
NeedsCompilation: yes
Depends: R (>= 3.4.0), fitdistrplus, stats, zipfR, actuar, triangle, mc2d
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Packaged: 2018-04-10 23:03:56 UTC; reddy_k
Repository: CRAN
Date/Publication: 2018-04-12 08:34:03 UTC

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Package spam64 updated to version 2.1-4 with previous version 2.1-3 dated 2018-03-29

Title: 64-Bit Extension of the SPArse Matrix R Package 'spam'
Description: Provides the Fortran code of the R package 'spam' with 64-bit integers. Loading this package together with the R package spam enables the sparse matrix class spam to handle huge sparse matrices with more than 2^31-1 non-zero elements.
Author: Reinhard Furrer [aut, cre], Florian Gerber [ctb], Roman Flury [ctb], Daniel Gerber [ctb], Kaspar Moesinger [ctb], Youcef Saad [ctb] (SPARSEKIT http://www-users.cs.umn.edu/~saad/software/SPARSKIT/), Esmond G. Ng [ctb] (Fortran Cholesky routines), Barry W. Peyton [ctb] (Fortran Cholesky routines), Joseph W.H. Liu [ctb] (Fortran Cholesky routines), Alan D. George [ctb] (Fortran Cholesky routines)
Maintainer: Reinhard Furrer <reinhard.furrer@math.uzh.ch>

Diff between spam64 versions 2.1-3 dated 2018-03-29 and 2.1-4 dated 2018-04-12

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New package openCR with initial version 1.1.1
Package: openCR
Type: Package
Title: Open Population Capture-Recapture
Version: 1.1.1
Depends: R (>= 3.2.0), secr (>= 3.1.5)
Imports: utils, MASS, nlme, parallel, stats, Rcpp (>= 0.12.14), stringr, plyr, abind, methods
LinkingTo: Rcpp
Suggests: knitr, RMark, rgdal
VignetteBuilder: knitr
Date: 2018-04-11
Authors@R: person("Murray", "Efford", email = "murray.efford@otago.ac.nz", role = c("aut","cre"), comment = c(ORCID = "0000-0001-5231-5184"))
Description: Functions for the analysis of capture-recapture data from animal populations subject to turnover. The models extend Schwarz and Arnason (1996) <DOI:10.2307/2533048> and Borchers and Efford (2008) <DOI:10.1111/j.1541-0420.2007.00927.x>, and may be non-spatial or spatial. The parameterisation of recruitment is flexible (options include population growth rate and per capita recruitment). Spatially explicit analyses may assume home-range centres are fixed or allow dispersal between sampling sessions.
License: GPL (>= 2)
LazyData: yes
LazyDataCompression: xz
NeedsCompilation: yes
Packaged: 2018-04-11 01:38:54 UTC; Murray
Author: Murray Efford [aut, cre] (<https://orcid.org/0000-0001-5231-5184>)
Maintainer: Murray Efford <murray.efford@otago.ac.nz>
Repository: CRAN
Date/Publication: 2018-04-12 08:48:29 UTC

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New package miceMNAR with initial version 1.0
Package: miceMNAR
Type: Package
Title: Missing not at Random Imputation Models for Multiple Imputation by Chained Equation
Version: 1.0
Date: 2018-04-11
Description: Provides imputation models and functions for binary or continuous Missing Not At Random (MNAR) outcomes through the use of the 'mice' package. The mice.impute.hecknorm() function provides imputation model for continuous outcome based on Heckman's model also named sample selection model as described in Galimard et al (2016) <doi:10.1002/sim.6902>. The mice.impute.heckprob() function provides imputation model for binary outcome based on bivariate probit model.
License: GPL-2 | GPL-3
Depends: R (>= 3.2.1), mice (>= 2.25)
Imports: stats, mvtnorm, pbivnorm, GJRM, sampleSelection
RoxygenNote: 6.0.1
NeedsCompilation: no
Author: Jacques-Emmanuel Galimard [aut, cre] (INSERM, U1153, ECSTRA team), Matthieu Resche-Rigon [aut] (INSERM, U1153, ECSTRA team)
Maintainer: Jacques-Emmanuel Galimard <jacques-emmanuel.galimard@inserm.fr>
Packaged: 2018-04-11 08:42:28 UTC; jegalimard
Repository: CRAN
Date/Publication: 2018-04-12 08:56:30 UTC

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Package bayesmeta updated to version 2.2 with previous version 2.1 dated 2018-02-06

Title: Bayesian Random-Effects Meta-Analysis
Description: A collection of functions allowing to derive the posterior distribution of the two parameters in a random-effects meta-analysis, and providing functionality to evaluate joint and marginal posterior probability distributions, predictive distributions, shrinkage effects, posterior predictive p-values, etc.
Author: Christian Roever [aut, cre], Tim Friede [ctb]
Maintainer: Christian Roever <christian.roever@med.uni-goettingen.de>

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